Broadband Hyperspectral Phase Retrieval From Noisy Data

Katkovnik, Vladimir; Shevkunov, Igor; Егиазарян, Карен

doi:10.1109/icip40778.2020.9191204

Cited by 3 publications

(4 citation statements)

References 18 publications

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“…The CCF algorithm is designed to deal with 3D complex-valued cube data and introduced in details in [31]. Examples of its application and features of this algorithm can be seen in [34], [44].…”

Section: Hs Complex Domain Phase Retrieval (Hsphr) Algorithmmentioning

confidence: 99%

“…i.e., the reference beam R t,k is not additive to the object as in (4) but propagates through the object U o,k [32], [33,34].…”

Section: Introductionmentioning

confidence: 99%

“…The solution for (4) can be given by FT of the observations combined with complex domain filtering [31]. The solution for ( 5) is obtained by FT of the observations included in the phase retrieval iterations [34].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

ADMM and Spectral Proximity Operators in Hyperspectral Broadband Phase Retrieval for Quantitative Phase Imaging

Katkovnik¹,

Shevkunov²,

Егиазарян³

2021

Preprint

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A novel formulation of the hyperspectral broadband phase retrieval is developed for the scenario where both object and modulation phase masks are spectrally varying. The proposed algorithm is based on a complex domain version of the alternating direction method of multipliers (ADMM) and Spectral Proximity Operators (SPO) derived for Gaussian and Poissonian observations. Computations for these operators are reduced to the solution of sets of cubic (for Gaussian) and quadratic (for Poissonian) algebraic equations. These proximity operators resolve two problems. Firstly, the complex domain spectral components of signals are extracted from the total intensity observations calculated as sums of the signal spectral intensities. In this way, the spectral analysis of the total intensities is achieved. Secondly, the noisy observations are filtered, compromising noisy intensity observations and their predicted counterparts. The ability to resolve the hyperspectral broadband phase retrieval problem and to find the spectrum varying object are essentially defined by the spectral properties of object and image formation operators. The simulation tests demonstrate that the phase retrieval in this formulation can be successfully resolved.

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Section: Hs Complex Domain Phase Retrieval (Hsphr) Algorithmmentioning

confidence: 99%

“…i.e., the reference beam R t,k is not additive to the object as in (4) but propagates through the object U o,k [32], [33,34].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

ADMM and Spectral Proximity Operators in Hyperspectral Broadband Phase Retrieval for Quantitative Phase Imaging

Katkovnik¹,

Shevkunov²,

Егиазарян³

2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…In the papers [8][9][10], we used an observation model where separate diffraction patterns were registered for separate wavelengths and masks. More close papers are [11,12], where we based our algorithms on the Fourier spectroscopy. In Ref.…”

Section: Introductionmentioning

confidence: 99%